Package edu.cmu.tetrad.search
Class TimeSeriesUtils
java.lang.Object
edu.cmu.tetrad.search.TimeSeriesUtils
Contains some utilities for doing autoregression. Should probably be improved
by somebody.
- Author:
- Joseph Ramsey, Daniel Malinsky (some improvements)
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Nested Class Summary
Nested Classes -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionstatic DataSetCreates new time series dataset from the given one with index variable (e.g., time)static booleanstatic DataSetstatic DataSetstatic DataSetcreateLagData(DataSet data, int numLags) Creates new time series dataset from the given one (fixed to deal with mixed datasets)static DataSetcreateShiftedData(DataSet data, int[] shifts) static DataSetdifference(DataSet data, int d) Calculates the dth difference of the given data.static intstatic KnowledgegetKnowledge(Graph graph) static intstatic StringgetNameNoLag(Object obj) static Stringstatic double[]getSelfLoopCoefs(DataSet timeSeries) static TimeLagGraphgraphToLagGraph(Graph _graph, int numLags) static TimeSeriesUtils.VarResultstructuralVar(DataSet timeSeries, int numLags) static doublesumOfArCoefficients(DataSet timeSeries, int numLags)
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Constructor Details
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TimeSeriesUtils
public TimeSeriesUtils()
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Method Details
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ar
- Returns:
- the VAR residuals of the given time series with the given number of lags. That is, every variable at the model lag is regressed onto every variable at previous lags, up to the given number of lags, and the residuals of these regressions for each variable are returned.
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ar2
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structuralVar
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createShiftedData
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getSelfLoopCoefs
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sumOfArCoefficients
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difference
Calculates the dth difference of the given data. If d = 0, the original data is returned. If d = 1, the data (with one fewer rows) is returned, with each row subtracted from its successor. If d = 1, the same operation is applied to the result of d = 1. And so on.- Parameters:
data- the data to be differenced.d- the number of differences to take, >= 0.- Returns:
- the differenced data.
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createLagData
Creates new time series dataset from the given one (fixed to deal with mixed datasets) -
addIndex
Creates new time series dataset from the given one with index variable (e.g., time) -
graphToLagGraph
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getNameNoLag
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getPrefix
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getIndex
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getLag
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getKnowledge
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allEigenvaluesAreSmallerThanOneInModulus
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